A Finite State Mobile Agent Computation Model

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1 A Finite State Mobile Agent Computation Model Yong Liu, Congfu Xu, Zhaohui Wu, Weidong Chen, and Yunhe Pan College of Computer Science, Zhejiang University Hangzhou , PR China Abstract In this paper, a novel formalized finite state mobile agent computation model based on the virtual organization is presented In this model, all the actions (eg service, migration and communication etc) of the mobile agents are treated as states The process of the mobile agents workflow is controlled by a finite-state-machine This ensures the atomic action for each mobile agent to avoid the abnormal condition of communication mismatch, which is very common in the traditional mobile agent systems 1 Introduction Mobile Agents are programs that can be migrated and executed between different network hosts They locate for the appropriate computation resources, information resources and network resources, combining these resources in a certain host to achieve the computing tasks [1] There are two types of mobile agents classified by the migration ability of the agents They are strong migration mobile agents (AgentTCL[6]) and weak migration mobile agents (Aglet[7]) When using the strong migration policy, the mobile agent system needs to record all the states and related data in each position of the agent, which will spend huge time and huge space on the transportation, and will lead to low efficiency When using weak migration policy, the transportation of data will decrease greatly, and the abilities of adapting the complicated network topology will decrease too Therefore, how to design a reliable and high-efficiency work pattern for the mobile agent becomes the key problem In fact, the grid [2] technology has provided a powerful platform for the mobile agent A serial of grid protocols [2,3], such as GNSP, GGMP, QDP, SAAP etc, make the new work pattern available In this paper, we introduce a finite state machine based mobile agent computation model whose ability of migration is between strong migration and weak migration In that model, the executing process has been divided into several states controlled by the finite state machine, and only the agent body and the communication data should be transported, so by this way, we improve the efficiency of transportation and the adaptation of mobile agent JX Yu, X Lin, H Lu, and Y Zhang (Eds): APWeb 2004, LNCS 3007, pp , 2004 Springer-Verlag Berlin Heidelberg 2004

2 A Finite State Mobile Agent Computation Model A Virtual Organization Based Architecture The requirements of communication with local hosts and communication with remote hosts cause the huge size of mobile agents, which will increase the data transportation In this paper, we introduce a virtual organization based communication method The remote communications are divorced from mobile agent bodies, using a virtual organization based fabric structure to realize the communications of remote nodes The mobile agents only care for the local communications with current position The local nodes in virtual organization are also regarded as the remote communication proxies 21 Virtual Organization The VO based architecture mentioned in this paper is a structure similar to the fabric layer in [2] The following part, some definitions are given out: Node, the minimized devices that can load and execute the mobile agents in network marked as R i There is a kind of nodes called Key Node, R 0 i, which deals with the remote communications Group, the set includes one node or several nodes, noted as G i ={ R 0, R 1, R 2,,,R n } The group can identify each node in VO, which means each node except key node will only belong to a certain group R i j means node belongs to group G j Group is a comparatively stable organization; the nodes belonging to certain group can leave this group and join another group dynamic The login and logout of nodes use a GGMP (Grid Group Management Protocol)[2], which is similar to the IGMP Node Distance, the least route number between two nodes, the Node Distance between node i and j marks as R i R j Virtual Organization, VO is a fabric structure that is composed of nodes and is established by a serial of protocols Normally, the group contains resembling and adjacent nodes There is a Key Node in each group, the Key Node in the group, G i, marks as R 0 i The function of key node in a group is similar to the gateway in a LAN, which communicates with other nodes outside the group A protocol called GNSP (Gateway Node Selective Protocol) [2] has been used to determine the key node Among all the nodes and groups, the key nodes constitute a virtual group called Kernel Group, G 0 It is the most important portion that serves for other nodes, deals with communication, seeking etc between nodes in virtual organization topology 22 Communication Algorithm between Nodes In VO architecture, the communication inside a group implement via broadcast, messaging to all the nodes in current group, only the nodes located in the same group with the message producer can receive the message, the other communications with outside nodes must be transmitted by the key node in current group Therefore, the communications of the VO architecture can be represented that, nodes in VO have been divided into several groups {G 0, G 1, G 2,,G n }, among those groups, G 0 is the

3 154 Y Liu et al kernel group, the communication algorithm between node R i j and node R p q is given as follow: Algorithm 1 Communication algorithm between nodes Step 1 The original node R i j sends out broadcast message, only the nodes in the group, G j, can receive it Step 2 If the destination node R p q lies on the same group, then the key node R 0 j discards the message and the communication ends, else go into step 3 Step 3 If the destination node does not lie on the same group, the key node, R 0 j, in the group G j sends a query message to all the key nodes in the kernel group, G 0, which query if the destination node R p q lies on the group Step 4 After the key nodes receive the query message, they will look up their group nodes table to find out the destination node If the destination node having R p q G q, there are two conditions, one is that the destination node is currently not available In this condition a node unavailable message is send back to the original node (group) The other condition is that the destination node is currently active, and then key node in G q replies the query message to destination key node, R 0 j If R p q G k, then G k will not reply query the message Step 5 If the original key node R 0 j, receives a destination node unavailable message, transmit it to the original node R i j, communication ends, else receives a hit message from G q, send the communication message to group G q when there is any reply message and time out, the original key node will discard or resend the message based on the privilege of the message Because the classification of group is according to the node distances and node functions, there will be much more frequent communication among the same group comparing to the communication between groups The cost of communication between groups is much more high than the local communication inside group, so the architecture can use the bandwidth more effectively And the virtual double layers (kernel group and normal groups) in VO can manage the node joining and leaving in a more intelligence architecture, solving the unstable topological problem in current network 3 Finite-State Mobile Agent Computation Model Finite-state mobile agent is a resource driven mobile agent system In fact, the mobile agent whose migration ability is between strong migration and weak migration can be seen as a finite-state machine auto motioning and driven by the resource and data To implement the VO based computation model, the first requirement is that the mobile agents can be executed in different nodes, so the finite-state mobile agent has been given out, in which the data and resource have been distinguished The definitions is presented as follow: Data is all the local data that will affect the mobile agent s state changing Resource is a general designation of all the data, device and software in VO nodes

4 A Finite State Mobile Agent Computation Model 155 In our model, all the run-time parameters and devices in remote nodes are called resources, which are different from the data affecting the mobile agent s state changing Therefore, we can ignore the influence of network topology to the executing of the mobile agents; we can only care for the state-changing of the mobile agents when they are executing and migrating, in other words, this mobile agent system needs not to care for which node does the mobile agent move from or move to, and the current state of mobile agent is the only parameter that should be recorded in that mobile agent, be migrated with mobile agent and be updated in time There are several parts, finite states, transition relation, exterior input symbols (data or resource) etc, which constitute a finite-state mobile agent The finite-state mobile agent marks as follow: FS-Agent = {A r, S r, U r, F r } A r is the identity of the mobile agent It will retain the identity value during the runtime, and the VO architecture can locate the right mobile agent by A r It can adopt a universal finite state set and common transition relation in practice service, such as virtual experiment device sharing service mobile agent, while the A r can be treated as an instance handle S r is the finite state set, including requesting state S 0, suspending state S 1, blocking state S 2, and service state Y 1, Y 2,, Y n The input symbols Ur include two conditions: one is the resource input symbol r i for service state Y i, the other one is the service time t i, the transition relation show in figure 1 t 1 Y 1 R S 1 r 1 S 0 T S 2 t n r n Y n Fig 1 Transition relations for finite state mobile agent 31 Finite-State Mobile Agent Computation Model (FS-MACM) After defining the finite-state mobile agent, we can give out the computation model for VO based mobile agent: VO based finite-state mobile agent computation model is a sixtuple FS-MACM = (R, S, M, Φ, v, E), where R is the node set, S is the finite state set of the mobile agent S does not include the state of the agent migration Λ and the null state ε Here, migration state Λ means that the mobile

5 156 Y Liu et al agent starts moving to another node to execute new state; null state ε means the mobile agent does not perform any action (executing and migration), M S is the set of all the message operation states for mobile agent M = {M s, M a }, M s is the state of sending message, M a is the state of receive message, v R is the initial node that the mobile agent has been produced, a mobile agent s service firstly comes from the node v, and then cycles driven by the finite states, E R is the set of final node for the mobile agent, only in the final node the mobile agent can be destroyed and the service ends, Φ, the transition relation, is a finite subset of (R X (S { Λ, ε} )) R: Φ : R X (S { Λ, ε} ) R, where (1) To all the R i, R j R, if Φ (R i, ε ) = R j, then R i = R j, (2) To all the R i, R j R, if Φ (R i, Λ ) = Rj, then R i R j, (3) To all the R i, R j R, S k S, if Φ (R i, S k ) = R j, then R i = R j, (4) To all the R i R, if Φ (R i, M a ) = R i, then the next transition state relation is Φ (R i, M s ) = R i In this computation model the migration state Λ is established by the communication of the nodes in VO Using the communication algorithm in section 22, mobile agent can move from the original node to the destination node efficiently The state transition and message communication are both implemented by this algorithm From the definition of the computation model, all the migration, communication (message method) and executing remote have been regarded as a state in computation model There is commonly a communication invalidation problem [4] in traditional message passing mobile agent systems, which is caused by the asynchronies of the mobile agent migration and the mobile agent message After the mobile agent sends out its message, it moves to another nodes, and then there may be a problem that the return message cannot find the position of the original agent Analogously, a broadcast based mode [5] for the mobile agent s seeking and communication has the problems such as huge transmitted data, easy to be block in finite bandwidth, and low reliability etc In our VO based computation model, the communication has been treated as states, and a serious of rules have been defined to ensure the symmetry of the sending message operation and receiving message operation, so the communication process and the migration process can be a atomic operation This will ensure the communication and migration to be sequence logic; there will not be the communication invalidation problem 32 Transition Forecast Algorithm in FS-MACM In VO based FS-MACM, data and resource are unified, so a minimized distance transition policy can be implemented, which can decrease the migration cost much The transition problem can be described as, In a node set {R 0, R 1, R 2,, R n }, when a mobile agent arrives at node R i, which node will be the next migration position for this mobile agent Here the algorithm is given as follow

6 A Finite State Mobile Agent Computation Model 157 Algorithm 2 Minimal distance transition forecast algorithm Step 1 The mobile agent serving in node R i finds a resource miss problem, which is there is not enough resource for the service continuing Step 2 Node R i broadcasts for the resource, only the node which has the resource that agent needs will reply this broadcast Step 3 When R i receives the reply messages, there will be possible-transition node set, {R 0, R 1,,R m }, the node contained in possible-transition node set has the resource that the mobile agent needs Calculating min{ R i R 0, R i R 1,, R i R m }, getting the minimal node distance R i R k, the node R k is the next migration node Step 4 Node move to node R k, algorithm ends 4 Conclusion This model is implemented in the Computer Support Cooperation Research project of China education ministry The groups are divided based on the research field of the center, the key nodes in each group is chosen, which constitute the kernel group The services in this CSCR platform are deployed as mobile agents, each service can be a mobile agent or several mobile agents and the service processes become states transition processes Once a mobile agent gets enough resource, the service will continue In this paper, a finite-state mobile agent computation model is presented to solve the problems in traditional mobile agent systems This model integrates the advantages of the strong-migration agent and the weak-migration agent, so that it can provide a more intelligent and robust mobile agent computation model that can avoid much frequently data transmitting With the aid of the virtual organization architecture, this computation model can effectually avoid the communication invalidation problem References 1 Tao, Xian-ping, Liu, Jian, and et al Mobile agent: a kind of future distributed computation model Computer Science, 1999, 26(2):1-6 2 Huang Lican, Wu Zhaohui, Pan Yunhe Virtual and Dynamic Hierarchical Architecture for E-Science Grid International Journal of High Performance Computing Applications, Volume 17 Issue 3- August I Foster, C Kesselman, S Tuecke The Anatomy of the Grid: Enabling Scalable Virtual Organizations International J Supercomputer Applications, 15(3), Tao, Xian-ping, Feng, Xin-yu, Li, Xin, and et al Communication mechanism in Mogent system Journal of Software, 2000, 11(8): Murphy, A, and Picco, GP Reliable communication for highly mobile agents In: Proceedings of Agent Systems and Architectures/Mobile Agents (ASA /MA) 99, CA, USA, 1999 pp Gray, RS Agent TCL: a transportable agent system Proceedings of International Conference on Information and Knowledge Management (CIKM 95) Workshop Intelligent Information Agents, Dec, Lange, D, and Oshima, M Programming Mobile Agents in Java - with the Java Aglet API

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